Wednesday, January 4, 2012

Alphabetical writing is something that was first introduced to me in a creative writing workshop as a way to improve your ability to express yourself within strict structural guidelines. Begin your first sentence with an 'A'-word, and complete a 26 sentence narrative using successive letters of the alphabet to begin each sentence. Coming up with a coherent story within these parameters is sometimes difficult, but can be rewarding if you choose your words carefully. During your story, you might find it advantageous to introduce key concepts, locations, or characters whose names begin with the more difficult letters of the alphabet (such as X, Y, and Z). Eventually, you will be comfortable enough with the limitations to express yourself freely in spite of the extremely specific format.

Furthermore, it is important to choose words that flow easily from one sentence to the next, rather than choosing a word that blatantly fills a requirement but sounds awkward. Generating specific words for each letter is much easier if you move the story along quickly, rather than talking in circles to thoroughly explain a few simple points as I am doing now. However, because this story serves as a tutorial in the exercise while at the same time meets the requirements that it in itself describes, I am forced to progress slowly. Including an Alphabetical story in the very format the instructions prescribe was an idea that came from an article that explained Socratic Dialogues through the use of Socratic dialogue. Just as easily, I hope this tutorial is serving the dual purpose of explaining the requirements while providing a sample piece.

Keep in mind that using the most common words will improve the overall flow of the story. Look for ways to begin sentences in a variety of ways, or consider using common expressions that will make the reader forget they are reading from a rigid structure. More importantly, be sure your story is fun and expressive! Name your characters, use descriptive language, create plot lines, and wrap everything up in only 26 sentences.

Oh, I almost forgot to mention, it's against the rules to use words from other languages unless the words are included in dialogue. Place quotation marks around the dialogue just as you would in any short story or essay. Questions always arise toward the end of the story, coupled with the inexplicable appearance of quails, xylophones, Volkswagen cars, and watermelons. Rather than sprinkling these in at the end, try your best to make them seem relevant to the plot. Since I’m never going to read your story, however, it's really none of my business how many quails you include. Try using quail for your Q sentence and just see how cheap you feel, and remember that I warned against it.

Using challenging exercises to improve, we are all capable of becoming great writers. Varying your sentence structure alone doesn’t make you a great writer—you have to have an acrobatic command of your thoughts and vocabulary (damn, vocabulary would have been a better V word to use). Whatever your purpose for attempting this exercise, remember that no one has a good X sentence, and there are only so many times you can talk about xylophones and get away with it. X-rays and xylophones—the end to nearly every Alphabetical story ever written (unless your story takes place in Zimbabwe). You can sit there for hours trying to come up with a good ending, but the end of the alphabet doesn't give you much to work with. Zooming along at a carefree pace in the beginning is replaced by a disheartening let down when you realize you should have named your character Xavier.

On the importance of institutional mission, James Lyons emphasizes the need to “know our tasks, which flow from many sources” (1997, p.136). In addition to knowing our tasks in the context of higher education administration, it is beneficial to borrow a bit of straightforward advice from Stephen Covey’s popular The 7 Habits of Highly Effective People, in which he reminds us to “begin with the end in mind” (1989). The ends that I will keep in mind throughout this idyllic prescription are the intended outcomes for a liberal undergraduate education.

Intended is a powerful modifier for the type of outcomes that college students should expect to gain by attending a four-year liberal arts college. I could have substituted the synonyms planned, envisioned, even wished-for to articulate how lofty these goals might seem to the 2 million unemployed Americans over 25 with at least a bachelor’s degree (Bureau of Labor Statistics, 2011). Herein lies a major discrepancy between the expectations of modern society and the espoused purposes of higher education at large. In a 1987 publication by the National Association of Student Personnel Administrators (as cited in Lyons, 1997), the traditional purposes of higher education are summarized as “to preserve, transmit and create knowledge, to encourage personal development and to serve society.” There is no mention of guaranteed jobs, fruitful employment, or satisfying careers to follow. However, because institutions of higher education operate within a society that demands opportunities for vocational advancement, such institutions should choose to accommodate this purpose by accepting it into their institutional missions. To turn their backs on this growing need would be a disservice to the communities in which the colleges and universities reside.

There is obviously more to college education than providing a competitive edge in the job search. As the feature in an article on contemporary unemployment, an underemployed graduate with two degrees in American Studies admits, “if I hadn’t received the kind of education I did, I would be less of an active citizen and less engaged in the world in ways I would not have discovered on my own” (Fairbanks, 2010). This anecdote highlights the previously mentioned purpose to serve society, and also alludes to an underlying self-discovery that should be a fundamental goal of higher education. Self-discovery and personal growth should remain crucial components of the college experience, and provide uniqueness to the institutional purpose that accounts for all manner of individual interests.

Before reaching my summary of the espoused purposes of higher education in a liberal college setting, it would be careless to neglect several documents that attempted to derive just such a list through years of collaboration and research. The Association of American Colleges & Universities (AACU), in a publication on College Learning for the New Global Century, describes the essential outcomes students should reach through college education: Knowledge, intellectual and practical skills, personal and social responsibility, and integrative learning (2007). In their publication of “Greater Expectations,” the AACU prescribes an “invigorated and practical liberal education” to impart the mastery of intellectual and practical skills, knowledge of the natural and social world, knowledge about forms of inquiry, and responsibility for personal actions and civic values (2002). Outcomes for liberal education vary only slightly from the purpose and intended outcomes of higher education as a whole, and reiterate themes of knowledge, intellectual and practical skills, and individual and social responsibility (AACU, 2005). In an address at the Annual Conference of the American Association for Higher Education, James Hunt Jr. proposed that the purpose of higher education in America is to promote citizenship, prepare people to be good human beings, and to educate people with world-competitive skills (1998). As Chair of The National Center for Public Policy and Higher Education, Hunt’s proposed purposes of higher education differ from the AACU’s consistent requisites, and focus on skills more than the transmission of knowledge. However, similarities between these lists of intended outcomes (Table 1) constitute what the AACU describes as a “remarkable consensus,” and provide a functional template for what the purpose of a liberal college education should include (AACU, 2005).

Table
1

The
purpose and intended outcomes of higher education

Knowledge

Intellectual and Practical Skills

Personal Development

Social Responsibility

College Learning for the New Global Century (AACU, 2007)

Knowledge of human cultures and the
physical and natural world

Intellectual and practical skills,
integrative learning

Personal responsibility

Social responsibility

Liberal Education Outcomes (AACU, 2005)

Knowledge of human cultures and the
natural world

Intellectual and practical skills

Individual responsibility

Social responsibility

Greater Expectations
(AACU, 2002)

Knowledge of the natural and social
world and about forms of inquiry basic to these studies

Mastery of intellectual and practical
skills

Responsibility for personal actions

Responsibility for civic values

Organizing for Learning (Hunt, 1998)

Educating people with
world-competitive skills

Preparing people to be good human
beings

Promote citizenship

NASPA, 1987

Preserve, transmit and create
knowledge

Encourage personal development

Serve society

Borrowing heavily from the consensus of intended outcomes prescribed over the past several decades (Table 1), and in light of the social demands that higher education serve as an avenue for vocational advancement, I believe the role of postsecondary education at a liberal arts college should include: A breadth of knowledge in arts and sciences, intellectual and practical skills that serve the individual and others, and the development of personally and socially responsible citizens. These broad themes include a variety of specific outcomes that merit closer examination in the following sections.

A breadth of knowledge in arts and sciences is an essential component of a liberal college education. A broad exposure to science, social sciences, mathematics, humanities, histories, languages, and the arts has several benefits beyond the retention of specific knowledge in each of these areas. A foundation in a diverse array of academic subjects “prepares graduates to think more broadly, to conceptualize at a multidisciplinary level that’s more responsive to the increasingly broad issues confronting people in all walks of life” (Herman, 2000). The importance of such a broad base is not in the memorization of discrete facts from a variety of fields, but in the ability to think between academic disciplines, draw inspiration from historical lessons, and develop meaning through the incorporation of multiple perspectives simultaneously.

In Forbes magazine, Mark Mills and Julio Ottino, a physicist and an engineer, endorsed humanistic training by suggesting “that the government funding agencies ought to support ‘whole-brain’ research agendas, as opposed to the usual ‘left-brain’ grant proposals” (as cited in Edelstein, 2010). Their recommendation comes with an awareness of “the attributes of the humanities found in right-brain thinking: creativity, artistry, intuition, symbology [sic], fantasy, emotions” (as cited in Edelstein, 2010). In combination, the resulting “whole-brain” thinking leads to the development of innovative thinking, a crucial skill that is difficult to teach directly. Innovative thinking, among other skills, is cultivated by exposure to a broad base of knowledge. Therefore, knowledge is the foundation rather than the endpoint in a liberal education that includes a multidisciplinary curriculum.

Innovative thinking is one of many intellectual and practical skills that serve the individual and others, which constitutes the second major theme in my summary of the purpose of higher education. In terms of vocational skills, innovative thinking is a highly prized skill for employees at all levels. A recent publication by MIT’s Sloan Management Review explains that innovation is no longer the responsibility of specialized divisions within corporations, but that innovation has increasingly been thought of as the responsibility of the entire organization (Birkinshaw, Bouquet, & Barsoux, 2011). Essentially, employees should constantly be searching for ways to improve, advance, and create new value. As mentioned by Mills and Ottino, this requires “whole-brain” thinking, which results from a liberal education. Aside from innovative thinking, there are a number of other specific skills that future employers will require. Returning to The Futurist predictions of Roger Herman:

In the years ahead we’ll need more and more workers who can think, collaborate, create, solve problems, communicate, and lead. Demand will be high for people who have learned how to learn; who have a strong multidisciplinary education; and who can adapt easily to whatever comes their way (2000).

Although Herman’s predictions pre-date the AACU’s Liberal Education Outcomes (2005), his recommendations touch on many of the specific skills noted by the organization; including written and oral communication, critical and creative thinking, teamwork, and a propensity for lifelong learning.

Intellectual and practical skills should be marketable to future employers, but should also serve the individual in everyday life. College graduates should be able to articulate their thoughts through written, spoken, and visual communication. They should be resourceful, and be able to navigate increasingly vast amounts of information available through interconnected technology. In order to make sense of this flood of information, graduates should be able to quickly filter through irrelevant content and apply a skeptical lens to unsupported claims. A graduate of a liberal education college will have the ability to work creatively with others to produce collaborative work that spans traditional academic disciplines. While these skills are not vocational skills per say, one can easily see how these skills translate into desirable employee characteristics. However, the inclusion of others into the description of this broad theme is not limited to future employers. There are many others in society that can benefit from the skills gained as a result of a liberal college education.

Remember back to the American Studies graduate who admitted that he would be a less active citizen and less engaged in the world if he had not received a liberal education. This call to civic engagement is a common theme among higher education outcomes, and is mentioned in all five of the summative lists outlined earlier. Civic values such as these may look different between individuals, but the common core seems to be a desire to use the skills acquired during college to affect positive change on one’s surroundings. This sense of empowerment is an important piece of the broader theme of developing personally and socially responsible citizens.

The AACU’s subset of outcomes under the header of individual and social responsibility includes civic responsibility and engagement, ethical reasoning, intercultural knowledge and actions, and propensity for lifelong learning (2005). While these are important traits that should result from a liberal education, I would expand this list to include a sense of empowerment, a belief that positive change is possible, and the rejection of passivity and complacency. These traits form what I refer to as the theme of developing personally and socially responsible citizens. There is an implied call to action in this theme, and an equally implied belief that positive changes are indeed possible. This call to action, partnered with a belief that change is possible, creates an enduring sense of optimism. Higher education should include these beliefs as intended outcomes for the betterment of the individual and society.

The order in which I have presented these themes was intentional, because I believe that there is a foundational dependency on the more basic elements that play a supportive role in helping graduates reach their personal and social potential (Figure 1). First, the breadth of knowledge in arts and sciences provides the base from which inspiration is drawn, through which perspectives can be challenged, and from which insights are formed. Second, the multidisciplinary knowledge is required in order for the individual to gain subsequent intellectual and practical skills that serve the individual and others. The “whole-brain” thinking is required for the full range of skills to be realized, and thus depends on the knowledge base. Finally, in order for the individual to develop into a personally and socially responsible citizen, they must possess a range of useful skills. In this way, the ability for the individual to continue developing personally and socially is dependent on the acquisition of skills, which in tern is dependent on the knowledge base.

Figure 1.Relationship between intended outcomes for a liberal undergraduate education. This figure illustrates the relative foundational aspects of each outcome theme.

A liberal undergraduate education does not operate independently of majors, but compliments the major with a well-rounded curriculum that provides a broad base of knowledge, as mentioned earlier. In terms of vocational preparation, the liberal education should provide flexibility rather than job training. Majors, in this sense, should be thought of as themes or sequences rather than job-ready specializations.

A broad range of coursework, the ability to think creatively, to adapt, and to merge knowledge from diverse areas will benefit future employees. In fact, a 2010 publication by the Bureau of Labor Statistics reports that Americans born between 1947-1964, and who received bachelor’s degrees, held around 11 jobs from age 18 to 44 (Bureau of Labor Statistics, 2010). Because of this volatility in employment, a flexible and innovative work force will be better prepared to navigate the labor market. In addition, Roger Herman argues that “the riches will go to those who have learned how to learn,” and that “a nucleus of permanent employees will manage the organization, drawing on a wide range of contingent labor … and outsourcing to accomplish the work to be done” (Herman, 2000). It is the purpose of a liberal four-year college to provide the flexible life-long learners who will occupy this nucleus of employees, whereas technical and vocational schools will provide the job-training outcomes for future contingent labor, or to supplement specific skills that are desired in a short amount of time. Four-year colleges with a liberal curriculum, as I have described, should cater to students looking for a profound opportunity to learn, develop, and innovate. In a sense, these students come to college waiting to develop and to be inspired, and are not seeking a purely pragmatic exchange of tuition for future job security. While other paradigms for higher education are developed and thrive in an increasingly occupational education industry, liberal undergraduate education should continue to impart a breadth of knowledge and skills that produce broadly empowered leaders.

References

Association of American Colleges & Universities. (2007). College learning for the new global century. Washington, DC: Author. Retrieved from http://www.aacu.org/advocacy/leap/documents/GlobalCentury_final.pdf

Association of American Colleges & Universities. (2002). Greater expectations: A new vision for learning as a nation goes to college. Washington, DC: Author. Retrieved from http://greaterexpectations.org

Bureau of Labor Statistics, U.S. Department of Labor. (2011, August). Employment status of the civilian population 25 years and over by educational attainment. Retrieved from http://www.bls.gov/news.release/empsit.t04.htm

Bureau of Labor Statistics, U.S. Department of Labor. (2010, September). Number of jobs held, labor market activity, and earnings growth among the youngest Baby Boomers: Results from a longitudinal survey. Retrieved from http://www.bls.gov/news.release/pdf/nlsoy.pdf

Covey, S. R. (1989). Habit 2: Begin with the end in mind. Retrieved from https://www.stephencovey.com/7habits/7habits-habit2.php

Edelstein, D. (2010). How is innovation taught? On the humanities and the knowledge economy. Liberal Education, 96(1). Retrieved from http://www.aacu.org/liberaleducation/le-wi10/le-wi10_Innovation.cfm

Hunt, J. B., Jr. (1998, June). Organizing for learning: The view from the governor’s office. The National Center for Public Policy and Higher Education. Retrieved from http://www.highereducation.org/reports/learning/learning.pdf

Tuesday, January 3, 2012

The first year of college is a contemporary milestone that brings with it opportunities and challenges as unique and diverse as the students themselves. Perhaps the challenges outweigh the opportunities, as only 73.9 percent of students in four-year public institutions persist to their second year of college, and only 55.9 percent of students in two-year colleges persist into their second year nationwide (American College Testing, 2010). Although these figures may be inflated by the frequency with which students transfer to other schools rather than dropout altogether, the numbers paint a tumultuous picture of the first-year experience. In response to these and similar findings, institutions have created a vast array of programs designed to ease the adjustment process for new students. Orientation sessions, learning communities, student mentors, peer counseling, bridge programs, and first-year seminars represent the variety of initiatives designed to set students up for success (Barefoot, 2000; Keup & Barefoot, 2005). Of these initiatives, first-year seminars are the most common, and can be found at over 87 percent of all colleges and universities (National Resource Center for The First-Year Experience and Students in Transition, 2009).

The term first-year seminar describes a variety of initiatives that vary by institution. The 2009 National Survey of First-Year Seminars found that over 40 percent of U.S. institutions offer extended orientation seminars as their primary first-year seminar type (National Resource Center, 2009). Other common initiatives included seminars with uniform academic content (16.1%), academic seminars on various topics (15.4%), hybrid courses (15.3%), and around 5 percent of institutions focused primarily on basic study skills (National Resource Center, 2009). Furthermore, these courses tended to be one semester in length (67.8%), taught by tenure-track faculty (61.4%), and counted for general education requirements (53.1%) (National Resource Center, 2009).

While first-year seminars come in many shapes and sizes, empirical studies on the subsequent outcomes indicate that the specific format is rather unimportant. For example, Friedman and Marsh investigated possible differences in outcomes between basic college success seminars, and thematic seminars (2009). They found no significant differences in retention rates or academic performance between students in thematic seminars and those in the seminars that generally focus on student transition and study skills (Friedman & Marsh, 2009). These findings seem to indicate that the type of first-year seminar is less important than the mere existence of the courses at all.

Outcomes for Participants / Nonparticipants

When comparing the outcomes for students enrolled in first-year seminar courses to those not enrolled in such courses, the benefits are undeniable. Pascarella and Terenzini summarized the literature and found “uniformly consistent evidence of positive and statistically significant advantages to students who take the courses” (2005, p. 400-401). Broadly, these advantages include increased persistence to the second-year of college (Porter & Swing, 2006; Starke & Sirianni, 2001), increased graduation rates (Schnell, Louis & Doetkott, 2003; Starke & Sirianni, 2001), and academic success (Keup & Barefoot, 2005; Reed, 2011; Starke & Sirianni, 2001).

Starke and Sirianni (2001) measured retention, academic achievement, bonding (to the college), and satisfaction between students in a first-year seminar course and students who did not take the course. Their results showed significant differences in third semester retention between students who took the seminar and those who did not. Seventy-nine percent of the students who took the course went on to their third semester at the same college, while only 51 percent of students not enrolled in the course returned following their second semester (Starke & Sirianni, 2001). Significant differences were also reported for graduation rates, with 50 percent of students enrolled in the first-year seminar graduating within six years compared to 20 percent of students not enrolled. Finally, cumulative GPA within four semesters of taking the course was significantly higher (M = 2.32 / M = 1.59) for students enrolled in the seminar compared to those who were not (Starke & Sirianni, 2001). Based on recent contributions to this expansive body of research, Pascarella and Terenzini’s summary (2005) holds true today:

Studies consistently find that [first-year seminar] participation promotes persistence into the second year and over longer periods of time. More recent studies employ various multivariate statistical procedures to control for academic ability and achievement and other precollege characteristics. Whatever the procedure, the research points to the same conclusion, indicating positive and statistically significant net effects of [first-year seminar] participation (versus nonparticipation) on persistence into the second year or attainment of a bachelor’s degree. (p. 402)

While these positive effects are evident in terms of persistence, graduation, and academic success, it remains unclear if the positive outcomes associated with first-year seminars are direct or indirect results of participation in the courses.

Course participation is related to a host of psychosocial and academic benefits that could be the underlying cause of the noticeable increase in persistence, graduation rates, and academic success. It has been shown that “course participants are more likely to report interacting with faculty and engaging in good classroom practices such as speaking up in classes, academic collaboration with other students, and course attendance” (Keup & Barefoot, 2005, p. 36). In addition to academic skills, students who took a first-year seminar course were more likely to engage in the campus community, and develop close friendships with other students. In another study, students who took a first-year seminar course showed improvements in attention, self-efficacy, and academic and general resourcefulness (Reed, Kennett, Lewis & Lund-Lucas, 2011). These outcomes have a positive influence on students’ perceived success and satisfaction with the institution, and could answer how first-year seminars are able to improve graduation rates, grades, and retention statistics (Keup & Barefoot, 2005). Early socialization, improved academic skills, regularly attending class, and interacting with faculty have already been established as ways to promote retention and academic success (Pascarella & Terenzini, 2005). Therefore, it remains unclear whether the benefits of first-year seminars are direct or indirect.

Conditional Effects and Individual Traits

Earlier reviews reported that “first-year seminars appear to benefit all categories of students,” including differences in gender, minority status, age, major, on/off campus, and at-risk status (Pascarella & Terenzini, 2005, p. 401). Recent studies have investigated possible conditional effects for students with learning disabilities (Reed et al., 2011) and varying high school achievement (Schnell et al., 2003). Some conditional effects were found, but it is important to note that differences only existed in the magnitude and not the direction of the relationship.

In a study of relative benefits for students with and without learning disabilities, Reed and colleagues used pre/post tests to survey students taking a first-year seminar course. All students reported significant improvements in inattentiveness, self-efficacy, academic resourcefulness, and general resourcefulness (Reed et al., 2011). Furthermore, “students with learning disabilities had higher gains in their academic self-efficacy than students without disabilities” (Reed et al., 2011). These findings show that trait differences can affect first-year seminar outcomes to a small extent.

Another study, focusing on graduation rates between students taking a first-year seminar course and a matched comparison group, found that around 40 percent of the seminar group graduated in 5 years or less, while the matched group only graduated 32 percent within 5 years (Schnell et al., 2003). The role of first-year seminars leading to improved graduation rates has already been established, however, the authors discovered an interesting relationship between high school achievement and the magnitude of the benefit received by the seminar. High school deciles were constructed to standardize student performance by controlling for the size of high schools students attended. Students in the lower to middle deciles benefited the most from taking the seminar, whereas students in the uppermost high school decile showed minimal benefit compared to students not enrolled in the seminar (Schnell et al., 2003).

Conceptual Model

These results demonstrate that, although first-year seminars have general positive effects that lead to persistence, graduation, and academic success for a variety of students, individual differences in traits and pre-college experiences still have an influence on student outcomes. This idea is conceptualized in a variety of models, but most simply in Astin’s (1991) Input-Environment-Output (I-E-O) framework (As cited in Keup & Barefoot, 2005). Astin’s framework is useful for considering biases resulting from the fact that characteristics and preferences students possess prior to attending college (inputs) can, and do, simultaneously influence the selection of environment and subsequent experiences in that setting (environment), and outcomes that result from both the environment and the initial inputs (Keup & Barefoot, 2005, p. 17-18). The influence pre-college experiences and individual traits have on the selection of the environment (particularly the selection of a first-year seminar course) draws attention to selection bias as yet another confounding factor in research regarding first-year seminars.

Selection Bias

Previously, researchers have attempted to control for selection bias through matched comparison groups (Porter & Swing, 2006; Schnell et al., 2003), comparison of required and elective seminar courses (Keup & Barefoot, 2005), and true experimental design. Matched comparison groups provide controls for potentially confounding pre-college variables in attempt to eliminate or reduce group differences. Such studies have controlled for gender, race, socioeconomic status, and academic ability, but rarely account for motivation for taking a seminar course and beliefs about college. When these variables are controlled, “advantages tend to shrink, although the benefits of [first-year seminar] participation remain” (Pascarella & Terenzini, 2005). These results suggest that conditional effects and individual traits account for some, but not all, of the positive outcomes associated with first-year seminars.

Looking at differences between required first-year seminar courses and elective courses, researchers found that “required first-year seminars do have an impact on key student outcomes” (Keup & Barefoot, 2005, p. 37). However, in the same study, multivariate analyses showed no statistically significant impact on adjustment to college for student electing to take the seminars. Paradoxically, this suggests that first-year seminars are more beneficial to students who do not choose to take them, and that students who are motivated to enroll in these seminars already possess the traits necessary to succeed.

Unfortunately, true experimental studies of first-year seminar courses are rare. A previous review of literature was only able to identify one such study by Strumpf and Hunt (As cited in Pascarella & Terenzini, 2005). This study was able to control for motivation to participate in a first-year seminar by randomly assigning students to two groups (course and no course) after they had already expressed interest in enrolling. While this procedure does not create intentionally similar groups, in theory it should provide a true experimental control for conditional effects, individual traits, and motivation. The researchers, in this case, reported significantly increased rates of persistence for students in the seminar group (As cited in Pascarella & Terenzini, 2005). Since this previous review, another experimental study was conducted by Yale (2000) at Bloomsburg University (As cited in Cuseo, in press) “in which students were assigned randomly to be course participants or non-participants” (p. 3). Results of this study revealed higher levels of academic and social integration for students in the seminar group. While only two experimental studies do little to establish a causal linkage between first-year seminar courses and outcomes, they do add to the weight of research that suggests participation in first-year seminars has either indirect or direct effects on factors leading to persistence, graduation, and academic success in college.

Implications for Student Affairs Professionals

Six years after the second volume of How College Affects Students (2005) was published, we are no closer to establishing causal links between first-year seminar courses and a multitude of beneficial outcomes. It is undeniable that first-year seminar courses have statistically significant and positive impacts on adjustment to college, the likelihood of persistence, eventual graduation, and academic success. However, it remains to be seen whether these positive impacts are the result of underlying dimensions producing an indirect effect on related outcomes, or direct links to substantial outcomes. While the academic question is tantalizing, from the viewpoint of a practitioner it may be irrelevant. Whether the positive impact is a direct or indirect result is inconsequential in light of the fact that first-year seminars at least contribute to sizeable improvements in student success.

Administrators can rest assured that first-year seminars have been thoroughly scrutinized, and that positive benefits are substantive. Cuseo provides the empirical case for first-year seminars in his own review of research-based outcomes. He concludes that “positive outcomes associated with the first-year seminar undoubtedly have been more carefully and consistently documented than have the outcomes of any other single course in the history of higher education.” (Cuseo, in press, p. 2).

Even more reassuring is the fact that vastly different types of first-year seminars at worst will minimally improve student retention, graduation, and academic success. In other words, these programs have a very low risk of negative consequences, but provide an enormous opportunity for promoting student success. Future research should focus on comparing the differences between seminar performance levels to identify best practices that have not been established empirically. Finally, rather than focusing on outcomes at the student or cohort level, research targeting campus-wide impacts will help identify the possibly subtle impact resulting from increased student involvement and social integration throughout the campus community.

Friedman, D. B., & Marsh, E. G. (2009). What type of first-year seminar is most effective? A comparison of thematic seminars and college transition/success seminars. Journal of the First-Year Experience and Students in Transition, 21(1), 29-42.

National Resource Center for The First-Year Experience and Students in Transition. (2009). 2009 National Survey of First‐Year Seminars. Retrieved from http://sc.edu/fye/research/survey_instruments/index.html

Monday, January 2, 2012

In 1965, Intel co-founder Gordon Moore forecasted the exponential growth of computer processing power by observing that transistor density on integrated circuits doubles about every two years (Intel Corporation, 2005). In the time it takes a comprehensive literature review of technology in higher education to be published, new innovations are likely to emerge. Since the arrival of the Information Age, technology has been synonymous with computing power, electronic devices, and digital information. Historically, however, technological advances in the form of stone points predate modern humans.

By definition, information technology has existed throughout recorded history. Ever since information was captured and transmitted through clay, stone, papyri, paper, and digital medium, modern technology has progressed to make the information readily available and easily accessible. Some view the increase in technology as a disruptive change that will revolutionize education, while others view academic institutions as slower to respond to the methodical creep of the Digital Age.

Because technological change involves major shifts in the way information is gathered, stored, and transmitted, implications for higher education are both urgent and unclear. Barry Mills speaks to the immediacy of the external environment’s encroachment on the doorstep of his institution: “I am convinced that we cannot responsibly ignore the changing dynamics in the way that information is stored and delivered, because these changing dynamics will undoubtedly change our role as educators” (2011). The scope of this paper is to identify how the already documented advances in technology affect colleges, how those institutions respond to the affect, and how changes in the technological features of higher education are managed.

Innovation, Adaptation, and Diffusion

Individuals within organizations bring ideas from the outside into their work routines (or create their own new ideas from within), those ideas change their routines, and the good ideas are transmitted to others in the institution. These affects alone are not changes to the organizational level, but a response to the presence and impact of technology. Themes of innovation, adaptation, and diffusion are strategies often described in relation to technological change (Kezar, 2001; Renes & Strange, 2011). Innovation can be defined as a product, process or procedure within an organization that is new, intentional, not routine, aimed at producing benefits, and having public effects (Kezar, 2001, p. 14). Innovations in the technology of higher education can either be introduced from the external environment or created within the organization. These new, intentional changes might take the form of tangible products (e.g. computers, hard drives, projectors, smartphones), processes (e.g. electronic assessment), or procedures (e.g. electronic course registration). Adaptation refers to modifications and alterations in response to changes in an external environment (Kezar, 2001). Adaptation narrowly describes the types of changes that occur within an evolutionary change model, which is discussed in the next section. Finally, diffusion models are an important consideration for how individuals adapt to innovations, though they do not adequately describe organizational change.

Kezar (2001) describes diffusion as a series of phases that individuals traverse, moving from awareness to interest, evaluation, trial, and finally adoption. Renes and Strange (2011) reviewed studies on motivations to use technology in teaching and found that individuals at different levels are more or less likely to embrace innovative change. Drawing on the work of Rogers (1995) and Hagner and Schneebeck (2001), they identified a variety of labels used to described how members of a social system adopt innovations. Rogers identified “innovators” and “early adopters” as those who begin using new technology within a system, followed by “early majority” and “late majority” adopters who are subsequently introduced to the innovation and may require evidence to encourage their adoption (as cited in Renes & Strange, 2011). Furthermore, in a study of 240 faculty members, Hagner and Schneebeck (2001) identified four groups based on individual motivation to adopt new technologies: Entrepreneurs, risk adversives, reward seekers, and reluctants (as cited in Renes & Strange, 2011). The largest group, risk adversives, is characterized by a lack of technical expertise, a fear of new teaching environments, and a hesitation to engage in self-examination.

The diffusion process as a description of the way individuals adapt to innovation does not accurately represent how change occurs at the organizational level. However, it is important to understand the characteristics of individual members because their aggregate experience with the diffusion of technology has an impact on the overall change process.

Theoretical Model of Technological Change in Higher Education

“Writing about [information technology] is like taking a snapshot of a marathon that has no clear rules, no clear route, and new competitors being added at odd times” (Barratt, 2003). This simile helps to describe technological change in “third period” terms, viewing change as a process rather than an episode, and without clear beginning or end (Demers, 2007, p. 115). The process view of organizational change is also reinforced anecdotally by the president of Bowdoin College, Barry Mills, who writes: “Technology… will have the power, potentially, to incrementally, rather than disruptively, improve our educational model” (2011).

Specifically, the theoretical model of change that most adequately describes the process of adaptation to technological change in higher education is the behavioral learning approach, which is grounded in the natural evolution perspective. Unlike the population ecology framework, organizational evolution acknowledges that organizations are capable of responding to changes either internally or externally, and that they are not simply outlived by fitter organizational models (Demers, 2007). Organizations learn by adapting routines, which is an experimental (i.e. trial and error) process emphasizing perceived stability and change (Demers, 2007, p. 123). These changes occur as a result of a continuous process in which organizations develop relatively fixed rules that are designed to incorporate feedback into their evolving relationship with the environment.

Although individuals working in an organization have individual thoughts and emotions, at the systemic level, the organization is capable of “learning” and adapting as a whole. When learning “occurs simultaneously at various collective levels” within an organization, it is capable of learning and adapting in spite of individual differences in its constituent parts (Burke, 2011, p. 79). Learning organizations also demonstrate a capacity to change while promoting systemic thinking, and involve “widespread participation of employees… in decision making, dialogue, and information sharing” (Burke, 2011, p. 79). Organizations engaging in behavioral learning account for the flexibility and lack of restrictive direction necessary to adapt to turbulent and fast-paced technological changes entering from the external environment.

Facilitating Technological Change

Studies examining factors that influence the implementation of technology within higher education incorporate “third period” perspectives that utilize informal bottom-up and individualized behavioral learning approaches. Nicolle and Lou (2008) found “peer support along with institutional support and perceived improvement in student learning were key influences” (As cited in Renes & Strange, 2011, p. 207). Furthermore, the same study found that discussing technological innovations during informal lunch meetings was more productive than formal training by technology staff members. Nicolle and Lou (2008) concluded, “when faculty members can see a clear personal benefit for themselves and see an increase in learning potential for their students, they are more likely to begin using technology” (As cited in Renes & Strange, 2011, p. 207). These findings connect with several principles for change strategies identified by Kezar (2001). By articulating and maintaining core characteristics (emphasis on student learning), and connecting the change process to individual identity (clear personal benefit for faculty), successful adoption of innovative technologies can occur.

At the annual conference of the Professional and Organizational Development (POD) Network, an interactive workshop produced a list of “roadblocks, obstacles, and speed bumps” that stand in the way of technological change (Bruff, Harapnuik, & Julius, 2011). The list includes faculty mistrust of technology, faculty needing examples for effective use of technology, and lack of cultural openness to try new technology (Bruff et al., 2011). In this list, faculty acting as the “late majority” and risk adversives reiterate the role of the individual in adapting to technological change. Kezar’s change principle for creating a culture of risk and changing belief systems (p. 121) aligns with a key feature of the “third period” behavioral learning approach: Search rules.

The behavioral learning approach utilizes routine-based change, and search rules can be thought of as routines for minor problem solving. That is, the routines influence the range of innovative alternatives that are available for choice (Demers, 2007, p. 124). There is a tendency for agents to refine existing technology rather than explore new technology, thereby playing it safe and reducing the risk of choice. To counter this conservative tendency, Kezar’s principle for creating a culture of risk will allow the adoption and invention of new routines.

Leading by Thermostat: Unfreezing, Changing, and Refreezing

The nature of technological change in higher education does not allow for accurate long-term planning. Therefore, organizational leadership could seek to manage the change process by regulating the thermostat. Using Lewin’s three step model of freezing, changing, and refreezing, Burke describes the actions that could facilitate change along these overlapping stages (2011).

Unfreezing – To successfully unfreeze an organization’s technological patterns, structures, and processes, a leader can promote change by increasing awareness of external developments. By drawing attention to the latest websites, services, gadgets, programs, and upgrades, a leader can help members at the individual level begin to experiment with new routines. Edgar Schein (1987) elaborated on Lewin’s stages, and described the creation of psychological safety as it pertains to the unfreezing process. He said that individuals need “to have no fear of retribution or punishment for embracing the change” (As cited in Burke, 2011, p. 166). Creation of psychological safety to engage in change is similar to Kezar’s principle for creating a culture of risk that was previously mentioned. Mark Milliron, president of the consulting group Catalyze Learning International, commented on technological change in higher education at a technology forum: “The worst thing in the world you can do is have a leadership team come down and say, ‘Damn it, innovate.’ I think you catalyze conversations and get people moving” (Arbogast, 2008). Milliron speaks to an essential component of change embodied by “third period” thinking; innovation has to happen at every level, and cannot merely be handed down by bold leaders.

Milliron continues:

I think people have figured out that the trickle-down theory of technology does not work. They have invested a ton of money in the innovators and have expected that the innovators will go do rowdy, great things, and then that would trickle down into goodness for the rest of the institution. And what they ended up with is a lot of segregation (Arbogast, 2008).

Changing – While Schein described changing as a cognitive restructuring, the change process of behavioral learning can be thought of as a systematic change in routine resulting from the integration of relatively fixed rules for continuously modifying the organization’s relationship with the external environment. So, while the change process is sufficiently described above, Schein’s description of Lewin’s change process can still provide useful guidelines for leaders. After unfreezing, the two processes necessary to promote change are the identification with a new vision, and scanning the environment for new relevant information (Burke, 2011). The leader could provide a new vision for adopting a certain process or piece of hardware. Additionally, the leader could align with a new routine or process and foster the diffusion of that idea to other individuals within the organization. If learning occurs at various simultaneous levels, then the organization itself can fundamentally change. Next, scanning the environment for new information would take the form of a search rule in the behavioral learning model. As in the case where faculty were more likely to adopt new technologies when they were introduced informally during lunch rather than at a training session hosted by IT staff, individuals engaging in a search for new routines will naturally go through a process of trial and error without being coaxed into a particular routine. This trial and error happens at the leadership level as well. Referring to online education, Richard Garrett, program director for the consulting group Eduventures, acknowledges that “everyone is experimenting; there is a lot of hype, a lot of possibility,” and concludes that the hype moves faster than the application of new technology, which, he says, does not have much velocity (Arbogast, 2008).

Refreezing – The integration of change consists of two parts, as identified by Schein (1987): “Helping the organizational member feel comfortable with the new behavior,” and “making sure that the new behavior fits well with others” (As cited in Burke, 2011, p. 167). These guidelines place a lot of emphasis on sustaining the change through reinforcing the new routines established at the individual level. The leader, in this case, can provide positive reinforcement to encourage the use of desired routines, and could relate new processes to core characteristics and personal identity to increase the chances of successful adoption of the new traits (Renes & Strange, 2011).

Conclusion

Technological change in higher education may seem both turbulent and incremental, depending on the frame of reference. At any given moment, the sheer pace of technological advances can seem quite chaotic and revolutionary. However, on a longer timeline, technological improvements are modeled as an exponential curve, and rarely make leaps (at least in terms of processing power) beyond what should be anticipated. On the other hand, although technological growth is steadily progressing, its characteristics are still largely unpredictable. As mentioned above, describing advances in technology is like taking a snapshot of a marathon with no clear course and no clear rules. In other words, while the pace is knowable, the direction, key players, and eventual outcomes are mysterious. Because of this nature, technological change in higher education can be viewed as grounded in the natural evolution perspective. Long-term forecasting is less beneficial, and institutions of higher education favor the flexibility to respond to the latest trends. However, these responses must be grounded at the individual level in order for the organization to “learn” and adapt to external changes. Because of this, the behavioral learning model is a helpful insight into the ways colleges change regarding technology.